A computer system may be used to identify current customers of a business enterprise who are at-risk of ending the customer's business relationship with the business enterprise. For example, a customer may end a business relationship by switching to a competitor of the business enterprise for the purchase of a desired product or a desired service. A customer also may end a business relationship by refraining from purchasing any products or services. The process by which a customer puts an end to a business relationship with a business enterprise may be referred to as churn. Churn also may refer to the process of continually losing customers, which requires a business enterprise to acquire new customers, some of which are lost, which requires a business enterprise to acquire more new customers, and so on. The loss of customers also may be referred to as customer attrition. Churn management refers to the process of helping to ensure that customers stay with a business enterprise.
To help manage customer churn, a computer system may be used to analyze customer behavior to identify patterns. The business enterprise then may be able to take appropriate action to reduce the number of customers who are lost.
For example, customers that are at risk of being lost may be identified by special analyses, including statistical analyses. The likelihood that a customer will not purchase products or services in the future may be determined. This likelihood may be referred to as a likelihood-to-churn. A customer at risk of churning may be referred to as having a high likelihood-to-churn. A customer with a high likelihood-to-churn may be identified based on having similar characteristics to customers that have already ended their relationships with the business enterprise. The ability to identify a customer with a high likelihood-to-churn may be advantageous, particularly when steps may be taken to reduce the number of customers who are lost. An analysis to identity the likelihood-to-churn of a customer also may be referred to as a customer loyalty analysis.
For example, in the telecommunications industry a customer may be able to switch from one telecommunication provider to another telecommunications provider relatively easily. A telecommunications provider may be able to identify, using data mining techniques, particular customers that are likely to switch to a different telecommunications provider. The telecommunications provider may be able to provide an incentive to at-risk customers to decrease the number of customers who switch.
Reducing the loss of customers is important to the profitability of a business enterprise. Reducing customer attrition may be particularly important when the cost of replacing a customer with another customer takes a significant amount of time to recover, as may be the case in the telecommunications industry. Thus, the churn of customers may be a costly problem to a business enterprise.